Ultimate, comprehensive review for big data warehousing for #OOW18.

This review is for everyone who either missed this year’s conference or just wants to relive the amazing experience all over again (but focusing on just the best bits obviously!). So here you go, my complete view nicely packaged and available free of charge in a number of different formats…

Following on from this year’s OpenWorld I have now put together the ultimate, comprehensive review for big data warehousing content from #OOW18. This free review contains the following information:

Key video highlights from the main executive keynotes

Overview of the announcements for Autonomous Database - contains the links you need to learn even more about how the Autonomous Database can simplify and speed up your big data warehousing projects!

Full list of Oracle Product Management and Development presenters, links to all their social media sites are included alongside each profile.

All the downloadable content from this year’s Must-See sessions and Hands-on Labs by the Oracle Product Management and Development teams.

All the links you need to keep up to date on Oracle’s strategy and products for Big Data Warehousing, SQL and SQL Analytics and Big Data. This covers all our websites, blogs and social media pages.

Comments

Post a Comment

Popular posts from this blog

Oracle RDBMS 11gR2 introduced the LISTAGG function for working with string values. It can be used to aggregate values from groups of rows and return a concatenated string where the values are typically separated by a comma or semi-colon - you can determine this yourself within the code by supplying your own separator symbol.

Based on the number of posts across various forums and blogs, it is widely used by developers. However, there is one key issue that has been highlighted by many people: when using LISTAGG on data sets that contain very large strings it is possible to create a list that is too long. This causes the following overflow error to be generated:ORA-01489: result of string concatenation is too long.
Rather annoyingly for developers and DBAs, it is very difficult to determine ahead of time if the concatenation of the values within the specified LISTAGG measure_expr will cause an ORA-01489 error. Many people have posted workarounds to resolve this problem - including mysel…

This post covers one of the new SQL performance enhancements that we incorporated into Database 12c Release 2. All of these enhancements are completely automatic, i.e. transparent to the calling app/developer code/query. These features are enabled by default because who doesn’t want their queries running faster with zero code changes?

So in this post I am going to focus on the new In-Memory “cursor duration” temporary table feature. Let’s start by looking at cursor duration temp tables…Above image courtesy of wikimedia.org
What is a cursor duration temp table?
This is a feature that has been around for quite a long time. Cursor duration temporary tables (CDTs) are used to materialize intermediate results of a query to improve performance or to support complex multi step query execution. The following types of queries commonly use cursor duration temp tables:WITH Clause and parallel recursive WITHGrouping SetsStar TransformationFrequent Item Set CountingXLATE
What happens during the …

Keith Laker

Keith Laker

Disclaimer

Opinions expressed are entirely my own and do not reflect the position of Oracle or any other corporation. Do NOT take anything written here, unless explicitly mentioned otherwise, to be Oracle policy or reflecting Oracle's support policy.

About Me

I have been working with Oracle data warehouse technology for over 20 years working on a wide variety of data warehouse projects both as a consultant and an onsite support engineer. I am now part of the Data Warehouse Product Management Team where I am responsible for analytical SQL. I am based in the UK at our Manchester office.

A key part of my role is to work with our sales teams to brief our customers on data warehousing and analytical SQL: explaining the wide variety of new and exciting opportunities that our DW and analytical solutions can support.

I regularly deliver sales training for data warehousing and analytical SQL across all our sales regions and provide competitive intelligence support across all the major data warehouse vendors.